Site Suitability Analysis for a Multi-Speciality Hospital Development in Indore

Abstract The selection of optimal multi-speciality hospital sites selection is a critical multi-criteria decision-making challenge in rapidly urbanizing regions especially Indore, directly impacting public health infrastructure and a need of a multi-speciality hospital in this city. Amid rising urban population densities, the demand for new medical facilities underscores the need for meticulous site selection. This paper presents a geospatial approach integrating Geographic Information Systems with multi-criteria decision-making techniques to identify suitable locations for new hospitals in Indore, India. The methodology overcomes limitations of subjective decision-making by providing a data-driven, objective framework . . Existing hospitals and Primary Health Centres were digitized and mapped in QGIS, revealing non-uniform coverage across the city. This includes urban factors like access to transportation networks like railways and bus ; and socio-economic aspects including population density, existing healthcare distribution, and other super speciality hospital. The research develops a spatial model using geospatial datasets to automate and prioritize potential hospital sites, systematically evaluating criteria such as population density and infrastructure to enhance accessibility and optimize our model. Ultimately, it equips urban planners with evidence-based insights to improve healthcare provision, promote sustainable development, and address spatial inequalities in developing regions. By tackling challenges like limited land availability and high costs in urbanizing areas, this GIS-based approach ensures strategic placement for maximum public benefit and operational efficiency offering governments and entrepreneurs a competitive edge through a new statistical model called Equitable Accessibility–Dominance Index (EADI). This non-linear, non-compensatory formulation robustly evaluates proximity, balance, and vulnerability, tackling healthcare complexities like distance to existing centres, service quality, and transport connectivity. And finally we got the best site by means of calculation and considering all the necessary factors. Keywords GIS, EADI, mapping, network analysis, geospatial